Blind Quality Assessment for Tone-Mapped Images by Analysis of Gradient and Chromatic Statistics
Blind Quality Assessment for Tone-Mapped Images by Analysis of Gradient and Chromatic Statistics
复制标题
通过梯度和色彩统计分析对色调映射图像进行盲质量评估
DOI：
10.1109/tmm.2020.2991528
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发表时间：
2021-01-01
影响因子：
7.3
通讯作者：
Li, Leida
中科院分区：
文献类型：
--
作者：
Fang, Yuming;Yan, Jiebin;Li, Leida
从高动态范围（HDR）图像获得的色调映射图像（TMI）会导致伪影和失真，这可能导致结构信息的丢失和颜色受损。通过分析TMIs的视觉特性，提出了一种鲁棒的基于梯度和色度统计的TMIs视觉质量盲评价方法（VQGC）。首先，基于人类视觉系统（HVS）对图像结构变化敏感的感知机制，我们采用梯度特征来度量TMI中的结构退化。为了准确地预测结构变形，我们计算梯度的大小和方向来衡量图像的结构变化，并计算相对梯度的大小和方向来捕捉微观结构的变化。其次，颜色不变性描述符被用来捕捉视觉退化的色彩由本地二进制模式（LBP）的四色特征地图。最后，梯度和色度特征结合在一起，作为最终的质量感知特征向量，这是应用于评估的TMI的感知质量的支持向量回归（SVR）。在公共数据库上的对比实验表明，该方法的性能优于现有的盲质量评估方法。
A tone-mapped image (TMI) obtained from the corresponding high dynamic range (HDR) image induces artifacts and distortion, which might result in the loss of structure information and impaired color. By analyzing the visual characteristics of TMIs, this work proposes a robust blind visual quality evaluation method for TMIs by using gradient and chromatic statistics (VQGC). First, motivated by the perceptual mechanism that the human visual system (HVS) is sensitive to image structure variation, we employ the gradient features to measure structure degradation in TMIs. To predict structure distortion accurately, we compute the gradient magnitude and orientation to measure image structure variation, and the relative gradient magnitude and orientation are also computed to capture microstructure change. Second, the color invariance descriptors are utilized to capture the visual degradation of colorfulness by local binary pattern (LBP) on four chromatic feature maps. Finally, the gradient and chromatic features are combined together as the final quality-aware feature vector, which is applied to assess the perceptual quality of TMIs by support vector regression (SVR). Comparison experiments show that the performance of the proposed method is better than other existing blind quality assessment methods on public databases.